Sistema de Computação Paralela e Distribuída Utilizando Raspberry Pi e Apache Hadoop

The term big data analytics refers to mining and analyzing of the voluminous amount of data in big data by using various tools and platforms. Some of the popular tools are Apache Hadoop, Apache Spark, HBase, Storm, Grid Gain, HPCC, Casandra, Pig, Hive, and No SQL, etc. These tools are used depending on the parameter taken for big data analysis. So, we need a comparative analysis of such analytical tools to choose best and simpler way of analysis to gain more optimal throughput and efficient mining. This chapter contributes to a comparative study of big data analytics tools based on different aspects such as their functionality, pros, and cons based on characteristics that can be used to determine the best and most efficient among them. Through the comparative study, people are capable of using such tools in a more efficient way.

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Big Data Analytics Tools and Platform in Big Data Landscape

10.4018/978-1-6684-3662-2.ch029 ◽

2022 ◽

pp. 622-631

Author(s):

Mohd Imran ◽

Mohd Vasim Ahamad ◽

Misbahul Haque ◽

Mohd Shoaib

Keyword(s):

Big Data ◽

Comparative Analysis ◽

Comparative Study ◽

Data Analytics ◽

Big Data Analytics ◽

Big Data Analysis ◽

Apache Hadoop ◽

Pros And Cons ◽

The Comparative Study ◽

Analytical Tools

The term big data analytics refers to mining and analyzing of the voluminous amount of data in big data by using various tools and platforms. Some of the popular tools are Apache Hadoop, Apache Spark, HBase, Storm, Grid Gain, HPCC, Casandra, Pig, Hive, and No SQL, etc. These tools are used depending on the parameter taken for big data analysis. So, we need a comparative analysis of such analytical tools to choose best and simpler way of analysis to gain more optimal throughput and efficient mining. This chapter contributes to a comparative study of big data analytics tools based on different aspects such as their functionality, pros, and cons based on characteristics that can be used to determine the best and most efficient among them. Through the comparative study, people are capable of using such tools in a more efficient way.

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Emerging Trends of Big Data in Cloud Computing

Applications of Big Data in Large- and Small-Scale Systems - Advances in Data Mining and Database Management ◽

10.4018/978-1-7998-6673-2.ch003 ◽

2021 ◽

pp. 38-55

Author(s):

Poonam Nandal ◽

Deepa Bura ◽

Meeta Singh

Keyword(s):

Cloud Computing ◽

Big Data ◽

Data Processing ◽

Open Source ◽

Software Framework ◽

Effective Solution ◽

Apache Hadoop ◽

Large Sets ◽

Exponential Increase ◽

Emerging Trends

In today's world where data is accumulating at an ever-increasing rate, processing of this big data was a necessity rather than a need. This required some tools for processing as well as analysis of the data that could be achieved to obtain some meaningful result or outcome out of it. There are many tools available in market which could be used for processing of big data. But the main focus on this chapter is on Apache Hadoop which could be regarded as an open source software based framework which could be efficiently deployed for processing, storing, analyzing, and to produce meaningful insights from large sets of data. It is always said that if exponential increase of data is processing challenge then Hadoop could be considered as one of the effective solution for processing, managing, analyzing, and storing this big data. Hadoop versions and components are also illustrated in the later section of the paper. This chapter majorly focuses on the technique, methodology, components, and methodologies adopted by Apache Hadoop software framework for big data processing.

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The importance of big data technology

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.5.21139 ◽

2018 ◽

Vol 7 (4.5) ◽

pp. 485

Author(s):

Samson Fadiya ◽

Arif Sari

Keyword(s):

Big Data ◽

Data Analytics ◽

Big Data Analytics ◽

Management Systems ◽

Apache Hadoop ◽

Industry Standard ◽

Data Framework ◽

Efficiency And Effectiveness ◽

Relational Database Management ◽

Big Data Technology

The adoption of Web 2.0 technologies, Internet of Things, etc. by individuals and organization has led to an explosion of data. As it stands, existing Relational Database Management Systems (RDBMSs) are incapable of handling this deluge of data. The term Big Data was coined to represent these vast, fast and complex datasets that regular RDBMSs could not handle. Special tools or frameworks were developed to deal with processing, managing and storing this big data. These tools are capable of functioning in distributed industry- standard environments thereby maintaining efficiency and effectiveness at a business level. Apache Hadoop is an example of such a framework. This report discusses big data, it origins, opportunities and challenges that it presents, big data analytics and the application of big data using existing big data tools or frameworks. It also discusses Apache Hadoop as a big data framework and provides a basic overview of this technology from technological and business perspectives.

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